Transcriptional and spatial profiling of the kidney allograft unravels a central role for FcyRIII+ innate immune cells in rejection

Rejection remains the main cause of premature graft loss after kidney transplantation, despite the use of potent immunosuppression. This highlights the need to better understand the composition and the cell-to-cell interactions of the alloreactive inflammatory infiltrate. Here, we performed droplet-based single-cell RNA sequencing of 35,152 transcriptomes from 16 kidney transplant biopsies with varying phenotypes and severities of rejection and without rejection, and identified cell-type specific gene expression signatures for deconvolution of bulk tissue. A specific association was identified between recipient-derived FCGR3A+ monocytes, FCGR3A+ NK cells and the severity of intragraft inflammation. Activated FCGR3A+ monocytes overexpressed CD47 and LILR genes and increased paracrine signaling pathways promoting T cell infiltration. FCGR3A+ NK cells overexpressed FCRL3, suggesting that antibody-dependent cytotoxicity is a central mechanism of NK-cell mediated graft injury. Multiplexed immunofluorescence using 38 markers on 18 independent biopsy slides confirmed this role of FcγRIII+ NK and FcγRIII+ nonclassical monocytes in antibody-mediated rejection, with specificity to the glomerular area. These results highlight the central involvement of innate immune cells in the pathogenesis of allograft rejection and identify several potential therapeutic targets that might improve allograft longevity.


Field-specific reporting
Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

Life sciences
Behavioural & social sciences Ecological, evolutionary & environmental sciences For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Life sciences study design
All studies must disclose on these points even when the disclosure is negative.
Sample size

Data exclusions
Replication Randomization All data produced in the present study are available. The Single-cell RNA-sequencing data have been deposited in BioStudies accession code E-MTAB-12051 (https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12051?accession=E-MTAB-12051). The images generated by MILAN were made available to the reviewers but are not accessible publicly. These image data can be made available upon reasonable request. The kidney transplant biopsy-derived signature matrix encompassing 18 cell types ("KTB18") generated for deconvolution is available in the Source data. This Signature matrix file can be directly used as custom input to run a job within the CIBERSORTx console (https://cibersortx.stanford.edu/runcibersortx.php). Source data are provided with this paper.
Sex-based analyses (comparison of the expression of sex-related genes within the cells) were performed in order to characterize the origin of the cells whenever a sex mismatch between the organ donor and the allograft recipient would exist (see supplementary figure 3). This study included both male and female participants. Sex annotation was based on selfreport. The number of samples for other analyses was too low to allow post-hoc disaggregation of the data by donor and recipient sex.
The population characteristics were presented in supplementary tables S1 and S2.
Single-cell RNA sequencing was performed on a cohort of 16 biopsies from 14 renal transplant recipients followed in the University Hospitals Leuven, Belgium (Supplementary Table 1). All transplantations were performed with negative complement-dependent cytotoxicity crossmatches on T and B cells. Most recipients had a planned indication biopsy with a high clinical probability for humoral rejection. For two patients, a follow-up biopsy was included in the study. For the multiplex immunofluorescence (MILAN) analysis, an independent set of 18 biopsies was included from renal transplant recipients followed in the University Hospitals Leuven, Belgium (Supplementary Table 2).
All patients provided written informed consent. This study was approved by the Ethics Committee of the University Hospitals Leuven (S64904).
No sample-size calculation was performed. We considered that 30,000 cells from more than 15 patients were sufficient for single cell RNA sequencing analysis and 500,000 cells from more than 18 patients for single cell immunostaining.
Data were excluded from the single cells transcriptomic according to the quality threshold based on mitochondrial gene representation as stipulated in supplementary figure 1.
The main transciptomic finding were replicated in external RNA sequencing datasets (figure 2F) and single cell RNA sequencing (supplementary figure 6). The in vitro experiments were performed at least 3 times independently with different donors. All attempts of replication are shown in the figures.
For neighborhood analysis, a quantitative analysis of cell-cell interactions was performed using an adaptation of the algorithm described in Schapiro et al. Briefly, for every cell, all the other cells that are located at a maximum distance d were counted. Then the tissue is randomized preserving the cytometry of the tissue as well as the X and Y coordinates of each cell but permutating the cell identities. This is repeated N times (here N = 1000) which allows to assign an empirical p-value by comparing the number of counts observed in the real tissue versus the number of counts in the randomized cases. Here we performed the described analysis for different values of the distance d (from 10 to 100 micrometers with a step of 10 micrometers) to show the consistency of the reported results. For all other experiments, no randomization was

Reporting for specific materials, systems and methods
We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response. For evaluation of intracellular expression of Galectin-9, cells were stained using a fixable viability dye (Fixable Viability Stain 780, BD Biosciences, France) and anti-CD45 BV510 (BD Biosciences) before fixation, permeabilization and staining using an Intracellular staining buffer set (Thermo Fisher Scientific) according to the manufacturer's instructions. Intracellular staining was performed for anti-Galectin-9 FITC (Miltenyi Biotec).
All antibodies used herein are commercially available and have been validated by their suppliers.